Digital Twin for Solar Biorefinery

The solar biorefinery concept combines multiple components — solar collectors, thermal energy storage (TES), hydrothermal reactors, and feedstock handling systems — into one integrated process. However, scaling this system for industrial use is limited by the absence of digital tools that can simulate, monitor, and optimize all subsystems in real time. The challenge is to design and implement a modular digital twin that can replicate the biorefineryʼs thermodynamic behavior, material flow, and energy efficiency under varying solar and operational conditions. This involves connecting sensors, IoT-based data acquisition, cloud computing, and machine learning for predictive maintenance, yield forecasting, and lifecycle optimization. Although driven by research at GÜNAM, this challenge addresses a clear industrial need: enabling solar-based biorefineries to operate efficiently, adapt to diverse feedstocks (e.g. fruit waste, livestock residues), and make data-driven decisions for process and investment planning.

Technology Readiness Level (TRL): 4 – Validated in laboratory environment; next steps involve pilot-scale integration and control testing.

Expected Outcomes: A digital twin platform capable of simulating full solar biorefinery operation, Enhanced process control, optimization, and predictive maintenance, Reduced downtime and operational uncertainty for industrial users, Stronger data-driven investment and sustainability planning

Impact on Operations: Implementing a digital twin will transform how solar-based bioenergy facilities are designed and managed. For industry, this means greater reliability, reduced operating costs, and higher confidence in scaling complex solar-integrated processes.

Previous Actions: Key ideas have been validated. Joint development and pilot testing of digital twin architectures; demonstration projects; and co-funded R&D proposals at EU, national, or bilateral levels.